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A semiparametric derivative estimator in log transformation models

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  • Chunrong Ai
  • Edward C. Norton

Abstract

This paper considers a regression model with a log-transformed dependent variable. The log transformed model is estimated by simple least squares, but computing the conditional mean of the dependent variable on the original scale given the explanatory variables requires knowing the conditional distribution of the error term in the transformed model. We show how to obtain a consistent estimator for the conditional mean and its derivatives without specifying the conditional distribution of the error term. The asymptotic distribution of the estimator is derived. The proposed procedure is then illustrated via a simulation study. Copyright The Author(s). Journal compilation Royal Economic Society 2008

Suggested Citation

  • Chunrong Ai & Edward C. Norton, 2008. "A semiparametric derivative estimator in log transformation models," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 538-553, November.
    • Handle: RePEc:ect:emjrnl:v:11:y:2008:i:3:p:538-553
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    4. Devon Wilson & Donald Dantzler & Damian Evans & Richard McGregory, 0. "Do Racial Disparities Exist in the Labor Market for Educators?," Journal of Economics, Race, and Policy, Springer, vol. 0, pages 1-10.
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    8. Ai, Chunrong & Li, Hongjun & Lin, Zhongjian & Meng, Meixia, 2015. "Estimation of panel data partly specified Tobit regression with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 316-326.
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    10. Zhong, Rong (Irene), 2018. "Transparency and firm innovation," Journal of Accounting and Economics, Elsevier, vol. 66(1), pages 67-93.
    11. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.

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